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Record W4321453576 · doi:10.7202/1096065ar

Listening at Night

2023· article· en· W4321453576 on OpenAlexaffvenue
Josh Dittrich

Bibliographic record

VenueEthnologies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsActive listeningSoundscapeEthnographySocial mediaCommodificationAppreciative listeningPsychologyKey (lock)SociologySociocultural evolutionMedia studiesAestheticsSound (geography)CommunicationAcousticsArtComputer science

Abstract

fetched live from OpenAlex

Drawing on ethnographic research with undergraduate students on their listening and sleeping practices, this essay develops a concept of “so(m)niferous media” to describe how listeners/sleepers use audio media to (re)mediate their experience of the night. The essay outlines key theoretical and practical affinities between sleeping and listening, taking a sociocultural approach to sleep informed by critical work in sound and media studies. Sleeping is reconceived as a sonically mediated, non-conscious experience of listening that participates ambivalently in the 24/7 logic of commodification outlined by Jonathan Crary and others. One unexpected finding of the ethnographic work is that many sleepers deliberately avoid obvious sound media products for sleeping (e.g., sleep playlists and podcasts, noise machines, “nature” sounds, binaural beats, etc) and seek out attention-grabbing social media content instead. Rather than lull themselves to sleep, listeners seem to want to engage their attention fully, while paradoxically shutting it down at the same time. So(m)niferous media thus seem to work directly on the attention of the listener, not the acoustic ambience of the sleeping space.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.210
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.248
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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